code: def generate_batch_infer_data(batch_ex, graph, samples):
      batch_test_samples = batch_ex[0]
      batch_test_labels = batch_ex[1]
  
      subgraphs = graphsage_sample(graph, batch_test_samples, samples)
      subgraph, sample_index, node_index = subgraphs[0]
  
      node_label = np.array(batch_test_labels, dtype="int64")
      return subgraph, sample_index, node_index, node_label
  
file_path: PGL/examples/gnn_depoly/node_classification_with_sampling/dataset.py
imports: import numpy
  import paddle
  from paddle.io import Dataset, DataLoader
  from pgl.sampling import graphsage_sample
label_desc: Use image node_id 1 for calling a global function with example usage: generate_batch_infer_data(batch_ex, graph, samples) and returns: subgraph,  sample_index,  node_index,  node_label